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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

X-ray tomography of feed-to-glass transition of simulated borosilicate waste glasses

The feed composition of a high level nuclear waste (HLW) glass melter affects the overall melting rate by influencing the chemical, thermophysical, and morphological properties of a relatively insulating cold cap layer over the molten phase where the primary feed vitrification reactions occur. Data from X ray computed tomography imaging of melting pellets comprised of a simulated high-aluminum HLW feed heated at a rate of 10°C/min reveal the distribution and morphology of bubbles, collectively known as primary foam, within this layer for various SiO 2 /(Li 2 CO 3 +H 3 BO 3 +Na 2 CO 3 ) mass fractions at temperatures between 600°C and 1040°C. To track melting dynamics, cross-sections obtained through the central profile of the pellet were digitally segmented into primary foam and a condensed phase. Pellet dimensions were extracted using Photoshop CS6 tools while the DREAM.3D software package was used to calculate pellet profile area, average and maximum bubble areas, and two-dimensional void fraction. The measured linear increase in the pellet area expansion rates – and therefore the increase in batch gas evolution rates – with SiO 2 /(Li 2 CO 3 +H 3 BO 3 +Na 2 CO 3 ) mass fraction despite an exponential increase in viscosity of the final waste glass at 1050°C and a lower total amount of gas-evolving species suggest that the retention of primary foam with large average bubble size at higher temperatures results from faster reaction kinetics rather than increased viscosity. However, viscosity does affect the initial foam collapse temperature by supporting the growth of larger bubbles. Because the maximum bubble size is limited by the pellet dimensions, larger scale studies are needed to understand primary foam morphology at high temperatures. This temperature-dependent morphological data can be used in future investigations to synthetically generate cold cap structures for use in models of heat transfer within a HLW glass melter.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Machine Learning–Guided Boolean Matrix Inference for Real-Time O-RAN Conflict Detection

Open Radio Access Networks (O-RAN) are emerging, software-driven cellular architectures that promote flexibility by enabling components from different vendors to interoperate. Multiple control applications called xApps can independently adjust network parameters in near real time, often without awareness of each other's actions. This creates a system highly prone to unintended conflicts and performance degradation due to the inherent complexity of such openness. To model such systems and ultimately prevent or mitigate xApp conflicts, it is essential to understand the dynamic relationships between xApps (A), the control parameters they adjust (P), and the resulting KPI responses (K). While the mappings from A to P and from K to A can often be derived from xApp specifications, the relationship from P to K is typically hidden within the system’s dynamics and must be inferred from observed data. We propose a novel data-driven Boolean inference framework that uncovers the hidden P?K dependencies using machine learning and interpretable rule induction. Continuous parameters and KPIs are first binarized using decision tree classifiers, and a binary influence matrix L is then inferred by solving Boolean matrix equations over time. This compact representation improves interpretability and enables real-time tracking of dynamically evolving parameter-KPI dependencies. We demonstrate the effectiveness of our method in a realistic mobile handover scenario, where it accurately recovers the underlying logic and enables proactive conflict detection.

42 - ENGINEERING↗
DOE OSTI2026

HostSub_GP: Precise Galaxy Background Subtraction in Transient Long-slit Spectroscopy with Gaussian Processes

We present a novel host galaxy subtraction technique in long-slit spectroscopy for extragalactic transients. Unlike classic methods which generally estimate the background using simple interpolation of local galaxy flux in the 2D spectrum, our approach leverages multi-band archival images of the host galaxies to model the background emission from the galaxy in the 2D spectrum. Such imaging encodes the wavelength-dependent galaxy profile along the slit, and is readily accessible through wide-field imaging surveys. We construct a smooth prior for the 2D galaxy profile with a Gaussian process (GP) based on these reference images, and use another GP to model the correlated deviations from the prior in the observed spectrum. This enables accurate inference of the galaxy flux blended with the transient. On synthetic long-slit data of a spiral galaxy extracted from a Multi Unit Spectroscopic Explorer hyper-spectral cube, the GP method remains robust as long as the host galaxy is spatially resolved and consistently outperforms classic methods. We apply the method to archival Keck spectra of two real transients, SN 2019eix and AT 2019qiz, to further demonstrate how the method uniquely recovers weak spectral features amid strong galaxy contamination, enabling refined constraints on the properties of both transients. We have released the software implementation, HostSub_GP, a scalable toolkit that leverages JAX, with an MIT license.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

A hybrid 3D/2D field response calculation for liquid argon detectors with PCB based anode plane

Liquid Argon Time Projection Chamber (LArTPC) technology is commonly utilized in neutrino detector designs. It enables detailed reconstruction of neutrino events with high spatial precision and low energy threshold. Its field response (FR) model describes the time-dependent electric currents induced in the anode-plane electrodes when ionization electrons drift nearby. An accurate and precise FR is a crucial input to LArTPC detector simulations and charge reconstruction. Established LArTPC designs have been based on parallel wire planes. It allows accurate and computationally economic two-dimensional (2D) FR models utilizing the translational symmetry along the direction of the wires. Recently, novel LArTPC designs utilize electrodes formed on printed circuit board (PCB) in the shape of strips with through holes. The translational symmetry is no longer a good approximation near the electrodes and a new FR calculation that employs regions with three dimensions (3D) has been developed. Extending the 2D models to 3D would be computationally expensive. Fortuitously, the nature of strips with through holes allows for a computationally economic approach based on the finite-difference method (FDM). In this paper, we present a new software package pochoir that calculates LArTPC field response for these new strip-based anode designs. This package combines 3D calculations in the volume near the electrodes with 2D far-field solutions to achieve fast and precise field response computation. We apply the resulting FR to simulate and reconstruct samples of cosmic-ray muons and 39 Ar decays from a Vertical Drift (VD) detector prototype operated at CERN. We find the difference between real and simulated data within 5%. Current state-of-the-art LArTPC software requires a 2D FR which we provide by averaging over one dimension and estimate that variations lost in this average are smaller than 7%.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

Used Nuclear Fuel Loading and Structural Performance Under Normal Conditions of Transport - Modeling, Simulation and Experimental Integration RD&D Plan

Under current U.S. Nuclear Regulatory Commission regulation, it is not sufficient for used nuclear fuel (UNF) to simply maintain its integrity during the storage period, it must maintain its integrity in such a way that it can withstand the physical forces of handling and transportation associated with restaging the fuel and moving it to treatment or recycling facilities, or a geologic repository. Hence it is necessary to understand the performance characteristics of aged UNF cladding and ancillary components under loadings stemming from transport initiatives. Researchers would like to demonstrate that enough information, including experimental support and modeling and simulation capabilities, exists to establish a preliminary determination of UNF structural performance under normal conditions of transport (NCT). This research, development and demonstration (RD&D) plan describes a methodology, including development and use of analytical models, to evaluate loading and associated mechanical responses of UNF rods and key structural components. This methodology will be used to provide a preliminary assessment of the performance characteristics of UNF cladding and ancillary components under rail-related NCT loading. The methodology couples modeling and simulation and experimental efforts currently under way within the Used Fuel Disposition Campaign (UFDC). The methodology will involve limited uncertainty quantification in the form of sensitivity evaluations focused around available fuel and ancillary fuel structure properties exclusively. The work includes collecting information via literature review, soliciting input/guidance from subject matter experts, performing computational analyses, planning experimental measurement and possible execution (depending on timing), and preparing a variety of supporting documents that will feed into and provide the basis for future initiatives. The methodology demonstration will focus on structural performance evaluation of Westinghouse WE 17×17 pressurized water reactor fuel assemblies with a discharge burnup range of 30-58 GWd/MTU (assembly average), loaded in a representative high-capacity (≥32 fuel rod assemblies) transportation package. Evaluations will be performed for representative normal conditions of rail transport involving a rail conveyance capable of meeting the Association of American Railroads (AAR) S-2043 specification. UNF modeling is anticipated to be defined to the pellet-cladding level and take in to account influences associated with spacer grids, intermediate fluid mixers, and control components. The influence of common degradation issues such as ductile-to-brittle-transition will also be accounted for. All model development and analysis will be performed with commercially available software packages exclusively. Inputs and analyses will be completely documented, all supporting information will be traceable, and bases will be defendable so as to be most useful to the U.S. Department of Energy community and mission. The expected completion date is the end of fiscal year (FY) 2013.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Measurement of acoustic properties of microalgae and implications for the performance of ultrasonic harvesting systems

Microalgae are a promising feedstock for biofuel production, but difficulties associated with harvesting suspended cultures contribute to the high costs of algal feedstock production. Ultrasonic harvesting has been identified as a potential low-cost technique, but limited data are available on the response of microalgae cells in the presence of an acoustic field. The acoustic radiation force acting on a cell depends upon cell size and the acoustic contrast factor (ACF) of the cell in the media. The ACF depends upon the density and compressibility of the cell and the media. Cell size and ACF were measured for Microchloropsis gaditana, Nannochloropsis oculata, Phaeodactylum tricornutum, and Chlamydomonas reinhardtii. The average ACFs, which were determined by measuring the densities and sound velocities of suspensions containing varying concentrations of cells in growth media, were 0.04 (range = 0.03–0.05) for M. gaditana, 0.02 (range = 0.01–0.04) for N. oculata, 0.05 (range = 0.04–0.07) for P. tricornutum, and 0.05 (range = 0.049–0.053) for C. reinhardtii. The ratio of the acoustic radiation force to the drag force would be highest for C. reinhardtii cells due to their larger effective radius (5.6 μm compared to 1.9–2.7 μm for the other species). The effective ACF of C. reinhardtii was also evaluated by recording the motion of cells in the presence of an acoustic field, using particle tracking velocimetry, and then modeling the recorded motion using COMSOL Multiphysics software. The result (ACF = 0.04) demonstrated agreement with the density/sound velocity meter method. Experiments with starch null sta6 mutant C. reinhardtii cells demonstrated that the effective ACF can transition from positive to zero and eventually become negative as microalgae cells accumulate lipids. Furthermore, the dynamic nature of the ACF represents an opportunity and a challenge for acoustic harvesting of algal cells.

09 BIOMASS FUELS↗
DOE OSTI2020

Excited-state electronic structure of molecules using many-body Green’s functions: Quasiparticles and electron–hole excitations with VOTCA-XTP

Here, we present the open-source VOTCA-XTP software for the calculation of the excited-state electronic structure of molecules using many-body Green’s function theory in the GW approximation with the Bethe–Salpeter equation (BSE). This work provides a summary of the underlying theory and discusses the details of its implementation based on Gaussian orbitals, including resolution-of-identity techniques and different approaches to the frequency integration of the self-energy or acceleration by offloading compute-intensive matrix operations using graphics processing units in a hybrid OpenMP/Cuda scheme. A distinctive feature of VOTCA–XTP is the capability to couple the calculation of electronic excitations to a classical polarizable environment on an atomistic level in a coupled quantum- and molecular-mechanics (QM/MM) scheme, where a complex morphology can be imported from Molecular Dynamics simulations. The capabilities and limitations of the GW–BSE implementation are illustrated with two examples. First, we study the dependence of optically active electron–hole excitations in a series of diketopyrrolopyrrole-based oligomers on molecular-architecture modifications and the number of repeat units. Second, we use the GW–BSE/MM setup to investigate the effect of polarization on localized and intermolecular charge-transfer excited states in morphologies of low-donor content rubrene–fullerene mixtures. These showcases demonstrate that our implementation currently allows us to treat systems with up to 2500 basis functions on regular shared-memory workstations, providing accurate descriptions of quasiparticle and coupled electron–hole excited states of various characters on an equal footing.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

A Cybersecurity Threat Profile for a Connected Lighting System

In anticipation of improved energy performance and cost savings, cities and building owners are increasingly considering “smart lighting initiatives” that aim to convert their collection of simple luminaires (i.e., lighting fixtures) into an intelligent connected lighting system (CLS) capable of remotely monitoring energy consumption and fault conditions, and possibly implementing adaptive lighting schemes. The U.S. Department of Energy (DOE) has set an national goal of tripling the energy efficiency and demand flexibility of the buildings sector by 2030, relative to 2020 levels 1. It is forecast that connected lighting systems can contribute to that goal by delivering 125 TWh of annual energy savings by 2035 2, equivalent to the annual output of 50 typical (500 MW) power plants. However, these energy savings and the DOE goal are put at significant risk if connected technologies are not adopted due to real or perceived cybersecurity concerns. Connected IoT devices such as these have historically been rife with vulnerabilities which sometimes put security considerations secondary to functionality and operability. What are the cybersecurity threats that will impact these systems, as formerly banal luminaires transition into intelligent connected devices that collect information about themselves, their surrounding environment, and possibly us? In this paper we analyze a threat profile performed on a fault-detection use case for streetlights. A threat profile establishes security requirements, justifies security measures, yields actionable controls, and effectively communicates risk to stakeholders. This effort provides critical information for making threat-based decisions to increase security at a reasonable cost, and can effectively be used by development teams, software architects, and managers to make cybersecurity a part of their ongoing culture of awareness, training, and prevention. This leads to more secure systems and better-understood security. On-premise, cloud, and hybrid architectures with different authentication mechanisms were modeled and later categorized using the Microsoft STRIDE framework. An analysis of the recommended controls for each threat was performed to determine which controls could and should be put in place by manufacturers or third-party suppliers, and which controls need to be left up the end-user to implement. Fifty-seven threats were identified. Among our key findings: (1) 65% (37/57) of the threats did not involve the luminaires, but rather the other components needed to communicate with and manage them; (2) 63% (36/57) of the threats could have been mitigated through manufacturer-implemented defensive techniques or “controls”; and (3) 23% (13/57) of the threats were dependent on the network configuration. Recommendations based on the results of this work are made to key stakeholder groups. Notably, lighting technology developers are advised to address all threats that can be reasonably controlled with baked-in technology solutions (e.g., encryption or authentication controls), and employ some form of secure supply chain management and tracking where other parts (e.g., sensors, microprocessors) of a luminaire must also be built and manufactured with the proper security controls in place. Developers should also review threats involving assets not developed in-house to understand how connectivity with other devices will affect their product during system operation and determine if a compensating control for a defense-in-depth strategy will be needed. Finally, those interested in deploying CLS should compare the differences between cloud and on-premise models to determine which is more suitable for their needs and the abilities of their security team.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Optimizing a Multiple Right-Hand Side Dslash Kernel for Intel Knights Corner

Lattice Quantum Chromo-dynamics (LQCD) stands unique as the only computationally tractable, non-perturbative, and model-independent quantum field theory of the strong nuclear force. LQCD achieves tractability by discretizing our familiar 4-dimensional space-time onto a hypercubic lattice. The core component of the linear solver used in LQCD is the Wilson-Dirac operator whose finite difference component is called the Dslash operator. Dslash is a nearest neighbor stencil operator summing matrix-vector multiplications over lattice points. The arithmetic intensity of a regular Dslash operator acting on a single vector in single precision is between 0.88-2.29 (depending on the tricks employed) making it memory bandwidth bound on most current architectures, including Xeon Phi. Maximizing the performance of Dslash on Xeon Phi requires deliberate exploitation of its architectural features. One key feature of Xeon Phi is its powerful vector processing unit with lengthy vector registers. There is a class of LQCD computations which aims to solve the Dirac equation for the same lattice gauge fields multiple times. In this case one can gain additional reuse of the gauge field, and potentially simplified vectorization, through applying Dslash to several vectors at the same time; often referred to as Multiple Right Hand Side (MRHS) Dslash. Previous work in this area focused on applying this approach to the Highly Improved Staggered operator, and in cases to the multi-Grid algorithm for Wilson clover fermions. Here, we present two approaches to MRHS Dslash: a vector register blocking approach and one using the software package QPhiX with a custom Code Generator for low-level intrinsics. We explore the Knights Corner instruction set, memory hierarchy, and threading capabilities. For standard lattice sizes used in testing, we observed significant speedups, with sustained performance of over 700 GFLOPS (single precision) in one instance. We achieved up to 27% of theoretical peak performance compared to a maximum of 12% obtained by the previous single RHS method in QPhiX.

Joó, Bálint↗
DOE OSTI2017

Improving nuclear power plant safety and operating margins through linear quadratic estimation - 290

Redundant measurement, trip, and actuation channels are required for reactor trips and engineered safety systems in nuclear power plants. There are three or four independent channels in existing plants, depending on the system. To prevent failures, consistent signals from any two channels together can trip the reactor or actuate safety systems. Measurements associated with safety trips and actuations include uncertainties related to the instruments making the measurements and to process conditions. Margins that include measurement uncertainties are set for each trip and actuation channel as though it were the only one taking action, thus preserving independence. There are sensors, however, that provide partially redundant information that could be used to decrease the uncertainty associated with measurements of plant conditions, while maintaining the three-channel redundancy important to plant safety. Reducing these uncertainties would both improve plant safety by providing more accurate knowledge of plant conditions and improve the operating margins that must take such uncertainties into account. This paper demonstrates how information that is already available to plant instrumentation and control systems and is already redundant can be used through software routines to reduce the error that must be taken into account in reactor trip and safety system actuation setpoints. Issues that would have to be addressed related to standards, licensing, and implementation are also discussed. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

Ice Load Project Final Technical Report

As interest and investment in offshore wind projects increase worldwide, some turbines will be installed in locations where ice of significant thickness forms on the water surface. This ice moves under the driving forces of wind, current, and thermal effects and may result in substantial forces on bottom-fixed support structures. The North and Baltic Seas in Europe have begun to see significant wind energy development and the Great Lakes of the United States and Canada may host wind energy development in the near future. Design of the support structures for these projects is best performed through the use of an integrated tool that can calculate the cumulative effects of forces due to turbine operations, wind, waves, and floating ice. The dynamic nature of ice forces requires that these forces be included in the design simulations, rather than added as static forces to simulation results. The International Electrotechnical Commission (IEC) standard[2] for offshore wind turbine design and the International Organization for Standardization (ISO) standard[3] for offshore structures provide requirements and algorithms for the calculation of forces induced by surface ice; however, currently none of the major wind turbine dynamic simulation codes provides the ability to model ice loads. The scope of work of the project described in this report includes the development of a suite of subroutines, collectively named IceFloe, that meet the requirements of the IEC and ISO standards and couples with four of the major wind turbine dynamic simulation codes. The mechanisms by which ice forces impinge on offshore structures generally include the forces required for crushing of the ice against vertical-sided structures and the forces required to fracture the ice as it rides up on conical-sided structures. Within these two broad categories, the dynamic character of the forces with respect to time is also dependent on other factors such as the velocity and thickness of the moving ice and the response of the structure. In some cases, the dynamic effects are random and in other cases they are deterministic, such as the effect of structural resonance and coupling of the ice forces with the defection of the support structure. The initial versions of the IceFloe routines incorporate modules that address these varied force and dynamic phenomena with seven alternative algorithms that can be specified by the user. The IceFloe routines have been linked and tested with four major wind turbine aeroelastic simulation codes: FAST, a tool developed under the management of the National Renewable Energy Laboratory (NREL) and available free of charge from its web site; Bladed[4], a widely-used commercial package available from DNV GL; ADAMS[5], a general purpose multi-body simulation code used in the wind industry and available from MSC Software; and HAWC2[6], a code developed by and available for purchase from Danmarks Tekniske Universitet (DTU). Interface routines have been developed and tested with full wind turbine simulations for each of these codes and the source code and example inputs and outputs are available from the NREL website.

17 WIND ENERGY↗
DOE OSTI2021

Autonomous experimentation systems for materials development: A community perspective

Solutions to many of the world's problems depend upon materials research and development. However, advanced materials can take decades to discover and decades more to fully deploy. Humans and robots have begun to partner to advance science and technology orders of magnitude faster than humans do today through the development and exploitation of closed-loop, autonomous experimentation systems. This review discusses the specific challenges and opportunities related to materials discovery and development that will emerge from this new paradigm. Our perspective incorporates input from stakeholders in academia, industry, government laboratories, and funding agencies. We outline the current status, barriers, and needed investments, culminating with a vision for the path forward. We intend the article to spark interest in this emerging research area and to motivate potential practitioners by illustrating early successes. We also aspire to encourage a creative reimagining of the next generation of materials science infrastructure. To this end, we frame future investments in materials science and technology, hardware and software infrastructure, artificial intelligence and autonomy methods, and critical workforce development for autonomous research.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Implementation Aspects of Smart Grids Cyber-Security Cross-Layered Framework for Critical Infrastructure Operation

Communication networks in power systems are a major part of the smart grid paradigm. It enables and facilitates the automation of power grid operation as well as self-healing in contingencies. Such dependencies on communication networks, though, create a roam for cyber-threats. An adversary can launch an attack on the communication network, which in turn reflects on power grid operation. Attacks could be in the form of false data injection into system measurements, flooding the communication channels with unnecessary data, or intercepting messages. Using machine learning-based processing on data gathered from communication networks and the power grid is a promising solution for detecting cyber threats. In this paper, a co-simulation of cyber-security for cross-layer strategy is presented. The advantage of such a framework is the augmentation of valuable data that enhances the detection as well as identification of anomalies in the operation of the power grid. The framework is implemented on the IEEE 118-bus system. The system is constructed in Mininet to simulate a communication network and obtain data for analysis. A distributed three controller software-defined networking (SDN) framework is proposed that utilizes the Open Network Operating System (ONOS) cluster. According to the findings of our suggested architecture, it outperforms a single SDN controller framework by a factor of more than ten times the throughput. This provides for a higher flow of data throughout the network while decreasing congestion caused by a single controller’s processing restrictions. Furthermore, our CECD-AS approach outperforms state-of-the-art physics and machine learning-based techniques in terms of attack classification. The performance of the framework is investigated under various types of communication attacks.

cross-layered↗
DOE OSTI2016

On the Strong Scaling of the Spectral Element Solver Nek5000 on Petascale Systems. In: EASC '16 Proceedings of the Exascale Applications and Software Conference 2016, Article No. 5

The present work is targeted at performing a strong scaling study of the high-order spectral element fluid dynamics solver Nek5000. Prior studies such as [5] indicated a recommendable metric for strong scalability from a theoretical viewpoint, which we test here extensively on three parallel machines with different performance characteristics and interconnect networks, namely Mira (IBM Blue Gene/Q), Beskow (Cray XC40) and Titan (Cray XK7). The test cases considered for the simulations correspond to a turbulent flow in a straight pipe at four different friction Reynolds numbers Reτ = 180, 360, 550 and 1000. Considering the linear model for parallel communication we quantify the machine characteristics in order to better assess the scaling behaviors of the code. Subsequently sampling and profiling tools are used to measure the computation and communication times over a large range of compute cores. We also study the effect of the two coarse grid solvers XXT and AMG on the computational time. Super-linear scaling due to a reduction in cache misses is observed on each computer. The strong scaling limit is attained for roughly 5000-10,000 degrees of freedom per core on Mira, 30,000 - 50,0000 on Beskow, with only a small impact of the problem size for both machines, and ranges between 10,000 and 220,000 depending on the problem size on Titan. This work aims at being a reference for Nek5000 users and also serves as a basis for potential issues to address as the community heads towards exascale supercomputers.

Offermans, Nicolas↗
DOE OSTI2014

SU-E-T-301: Spectral Comparison of the Xoft and Zeiss 50 KVp X-Ray Systems

Purpose: To compare x-ray spectra of the 50 kVp Xoft Axxent™ and Zeiss INTRABEAM™ x-ray sources after filtration by saline-filled balloons applicators or spherical polymer applicators, respectively. Methods: Measurements were made for 3.5, 4.0 and 5.0 cm diameter applicators using an AmpTek model XR-100T-CdTe cadmium telluride spectrometer with 100 μm diameter collimating aperture and model PX4 digital pulse processor. Spectra were then corrected for escape processes using AmpTek XRF-FP Escape software. Both Axxent and INTRABEAM sources were operated at 50 kV and 40 μA to eliminate pulse saturation. The balloon or spherical applicator was placed in a centering fixture in contact with the collimator cap. The distance through the collimator housing from the applicator surface to the spectrometer's beryllium entrance window was nominally 52mm. Approximately 500,000 counts were collected for each spectrum. Results: Measured spectra in all cases had a broad Bremsstrahlung continuum with subtle differences in characteristic low energy x-rays lines from the different materials used for the anode thin films and substrates. After corrections for escape events average energies were calculated for spectra emerging from applicators. The average energies were 28.2 ±0.3 keV, 29.0±0.7 keV, and 31.7±0.9 keV for the 3.5, 4.0 and 5.0 cm diameter applicators, respectively. Differences in average energies ranged from 2.0 to 5.6% for these diameters. The mean energies of the spectra are more dependent on balloon size than on the delivery system used. Conclusion: Energy spectra at the surfaces of 3.5, 4.0 and 5.0 cm diameter applicators were measured for the Axxent and INTRABEAM x-ray systems were using a Cd-Te spectrometer. The average energies of the two x-ray systems for comparable applicator sizes were within 5.6%, and as little as 0.6 keV difference for the smaller applicator size. Research sponsored by Xoft, a subsidiary of ICAD.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

VUSAT - A VERA-CS Uncertainty and Sensitivity Analysis Toolkit

VERA-CS (the Virtual Environment for Reactor Applications, Core Simulator) is a high-fidelity multiphysics core simulator under development by the Consortium for Advanced Simulation of Light Water Reactors (CASL). VERA-CS includes three main components: MPACT for reactor physics and neutron transport, COBRA-TF for thermal-hydraulics, and ORIGEN for isotopic depletion. VERA-CS has been applied to an array of problems including core physics analysis, and the modeling for all of the fuel cycles of Watts Bar Nuclear Unit 1 (WBN1). MPACT is a 3D pin-resolved reactor transport code developed by Oak Ridge National Laboratory (ORNL) and the University of Michigan. COBRA-TF (CTF) is a three-field two-phase flow subchannel analysis code developed by ORNL and North Carolina State University. CTF solves the mass, momentum, and energy equations for the liquid, vapor, and droplet phases for each subchannel in the core and captures the axial flow within each channel as well as cross-flow between channels. Direct coupling between neutronics (MPACT) and thermal-hydraulics (CTF) in VERA-CS provides temperature and density feedback. CTF includes a number of models important for LWR safety and design analysis including flow regime dependent two-phase wall heat transfer, inter-phase heat transfer and drag, droplet breakup, and quench-front tracking. ORIGEN is developed by ORNL and released through the SCALE package. ORIGEN is directly integrated in MPACT through its API to calculate the changes in nuclides for every depletable cross-section region. Uncertainties exist in safety calculations with computer codes for nuclear reactor modeling and simulation, and they come from code limitations, scaling inaccuracies embedded in the experimental data, and uncertainties associated with the state of the reactor at the initiation of the transient. Consequently, for applications of high fidelity calculations using VERA-CS, proper uncertainty quantification (UQ) and sensitivity analysis (SA) of the computing models of reactor neutronics and thermal-hydraulics are important to comprehensively understand the results. New methods in UQ and SA have to be developed in multi-physics calculations using VERA-CS. Toward this end, a software package called VUSAT which stands for VERA-CS Uncertainty and Sensitivity Analysis Toolkit has been developed to facilitate the applications of VERA-CS within the context of best estimate plus uncertainty (BEPU) analysis framework. In this work, the VUSAT application to analyze departure from nucleate boiling (DNB) is presented.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Active learning for accelerated design of layered materials

Hetero-structures made from vertically stacked monolayers of transition metal dichalcogenides hold great potential for optoelectronic and thermoelectric devices. Discovery of the optimal layered material for specific applications necessitates the estimation of key material properties, such as electronic band structure and thermal transport coefficients. However, screening of material properties via brute force ab initio calculations of the entire material structure space exceeds the limits of current computing resources. Moreover, the functional dependence of material properties on the structures is often complicated, making simplistic statistical procedures for prediction difficult to employ without large amounts of data collection. Here, we present a Gaussian process regression model, which predicts material properties of an input hetero-structure, as well as an active learning model based on Bayesian optimization, which can efficiently discover the optimal hetero-structure using a minimal number of ab initio calculations. The electronic band gap, conduction/valence band dispersions, and thermoelectric performance are used as representative material properties for prediction and optimization. The Materials Project platform is used for electronic structure computation, while the BoltzTraP code is used to compute thermoelectric properties. Bayesian optimization is shown to significantly reduce the computational cost of discovering the optimal structure when compared with finding an optimal structure by building a regression model to predict material properties. The models can be used for predictions with respect to any material property and our software, including data preparation code based on the Python Materials Genomics (PyMatGen) library as well as python-based machine learning code, is available open source.

36 MATERIALS SCIENCE↗
DOE OSTI2022

tapir: A tool for topologies, amplitudes, partial fraction decomposition and input for reductions

The demand for precision predictions in the field of high energy physics has dramatically increased over recent years. Experiments conducted at the LHC, as well as precision measurements at the intensity frontier such as Belle II require equally precise theoretical predictions to make full use of the acquired data. To match the experimental precision, second-, third- and, for certain quantities, even higher-order calculations in perturbative quantum field theory are required. To facilitate such calculations, computer software automating as many steps as possible is required. Yet, each calculation poses different challenges and thus, a high level of configurability is required. In this context we present tapir: a tool for identification, manipulation and minimization of Feynman integral families. It is designed to integrate in toolchains based on the computer algebra system FORM, the use of which is common practice in the field. tapir can be used to reduce the complexity of multi-loop problems with cut-filters, topology mapping, partial fraction decomposition and alike. Program Title:tapir CPC Library link to program files:https://doi.org/10.17632/ptc9t46xyn.1 Developer's repository link:https://gitlab.com/tapir-devs/tapir Licensing provisions: GPLv3 Programming language:python 3, C++ Nature of problem: Multi-loop computations require the automatization of a large number of different tasks related to Feynman integral topologies. Among them are the identification and minimization of integral topologies, partial fraction decomposition of topologies in the case of linearly dependent propagators as well as mapping scalar products of loop momenta to scalar functions. Solution method: The minimization of topologies is performed by comparison of their respective Nickel indices [1], even further minimization utilizes Pak's algorithm [2]. To efficiently map scalar products of loop momenta to scalar functions FORM [3] code is generated. Additional comments including restrictions and unusual features: Minimization based on Pak's algorithm slows down for many lines and scales. A coarser minimization using the Nickel indices, however, is still possible. [1]B. Nickel, D. Meiron, G.A.J. Baker, Compilation of 2-pt and 4-pt graphs for continuous spin model, Report, University of Guelph, 1977.[2]A. Pak, J. Phys. Conf. Ser. 368 (2012) 012049, https://doi.org/10.1088/1742-6596/368/1/012049, arXiv:1111.0868.[3]B. Ruijl, T. Ueda, J. Vermaseren, FORM version 4.2, arXiv:1707.06453, 7 2017.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗